Companies that adopt industrial artificial intelligence see productivity losses before longer-term gains, according to new research.
Differences in AI adoption in Europe and the US: Explanations and implications for productivity growth
The economic impact of generative AI will depend on the speed and breadth of adoption by workers and firms. Drawing on a survey of workers in the US and six European countries and a firm survey covering 32 European countries, this column explores the speed of AI adoption across countries and whether an ‘AI gap’ will exacerbate existing productivity differences between the US and Europe. There are large differences in AI adoption across countries, much of which are accounted for by management practices. Higher AI adoption rates are associated with faster productivity growth but not with changes in employment.
The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)
Early AI adoption in U.S. manufacturing produced a J-curve pattern of short term productivity loss followed by medium term growth – though quite unevenly.
Mind the Gap: AI Adoption in Europe and the U.S.
This paper combines international evidence from worker and firm surveys conducted in 2025 and 2026 to document large gaps in AI adoption, both between the US and Europe and across European countries. Cross-country differences in worker demographics and firm composition account for an important share of these gaps. AI adoption, within and across countries, is also closely linked to firm personnel management practices and whether firms actively encourage AI use by workers. Micro-level evidence suggests that AI generates meaningful time savings for many workers. At the macro level, in recent years industries with higher AI adoption rates have experienced faster productivity growth. While we do not establish causality, this relationship is statistically significant and similar in magnitude in Europe and the US. We do not find clear evidence that industry-level AI adoption is associated with employment changes. We discuss limitations of existing data and outline priorities for future data collection to better assess the productivity and labor market effects of AI.
Companies Are Being Torn Apart by AI "Workslop," Stanford Research Finds
Not only is AI hampering productivity, but it's also blowing up collaboration and souring employee dynamics.
The AI productivity myth is more harmful than you think
Perceived productivity may be up thanks to AI, but there's debt collecting in the shadows.
Thousands of CEOs admit AI had no impact on employment or productivity—and it has economists resurrecting a paradox from 40 years ago | Fortune
In the 1980s, economist Robert Solow made an observation that reminded economists of today’s AI boom: “You can see the computer age everywhere but in the productivity statistics.”
Thousands of CEOs just admitted AI had no impact on employment or productivity—and it has economists resurrecting a paradox from 40 years ago | Fortune
In the 1980s, economist Robert Solow made an observation that reminded economists of today’s AI boom: “You can see the computer age everywhere but in the productivity statistics.”
Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford
AI boosts worker productivity — but does that translate to final outputs? | MIT Sloan
A new study found that developers using AI tools can write much more code than those working without AI, but they don’t release as much new software.
Why the tech industry can't keep up with the AI backlash
AI's externalities are growing faster than the industry can address them
Tech companies are cutting jobs and betting on AI. The payoff is far from guaranteed
AI experts say we’re living in an experiment that may fundamentally change the model of work
The Productivity Is Real. The Scaling Isn't.
What running an AI agent team taught me about why organizations can't do what one person can.
Do AI-enabled companies need fewer people? | Seldo.com
AI-native startups are doing more with less — 40% smaller teams, 6x higher revenue per employee — and the data confirms it's not just hype. But the wave of new jobs I predicted hasn't materialized so far. Compute is replacing labor. Will that change?
When everyone has AI and the company still learns nothing
Are people using AI, or is the organization learning from it? What changed because we spent those tokens? And who moves discoveries from individuals to teams to organizational capabilities?
A Bick, A Blandin, D Deming, N Fuchs-Schündeln, & J Jessen find large differences in AI adoption across countries, much of which are accounted for by management practices. Higher adoption rates are associated w/ + productivity growth but not w/ employment changes. cepr.org/voxeu/columns/differences-ai-… #EconSky
